This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Electronic Health Records (1053) Cancer Epidemiology, Cancer Surveillance and Infodemiology (77)

Published on in Vol 21, No 5 (2019): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13260, first published .
Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine

Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine

Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine

Authors of this article:

Xiaofang Wang1, 2 Author Orcid Image ;   Yan Zhang3 Author Orcid Image ;   Shiying Hao4, 5 Author Orcid Image ;   Le Zheng4, 5 Author Orcid Image ;   Jiayu Liao6, 7 Author Orcid Image ;   Chengyin Ye8 Author Orcid Image ;   Minjie Xia9 Author Orcid Image ;   Oliver Wang9 Author Orcid Image ;   Modi Liu9 Author Orcid Image ;   Ching Ho Weng2 Author Orcid Image ;   Son Q Duong10 Author Orcid Image ;   Bo Jin9 Author Orcid Image ;   Shaun T Alfreds11 Author Orcid Image ;   Frank Stearns9 Author Orcid Image ;   Laura Kanov9 Author Orcid Image ;   Karl G Sylvester2 Author Orcid Image ;   Eric Widen9 Author Orcid Image ;   Doff B McElhinney4, 5 Author Orcid Image ;   Xuefeng B Ling2, 5 Author Orcid Image
Article Authors Cited by (32) Tweetations (4) Metrics

Journals

  1. Karhade A, Bongers M, Groot O, Cha T, Doorly T, Fogel H, Hershman S, Tobert D, Schoenfeld A, Kang J, Harris M, Bono C, Schwab J. Can natural language processing provide accurate, automated reporting of wound infection requiring reoperation after lumbar discectomy?. The Spine Journal 2020;20(10):1602 View
  2. Zhou K, Hu Y, Pan H, Kong L, Liu J, Huang Z, Chen T. Fast prediction of reservoir permeability based on embedded feature selection and LightGBM using direct logging data. Measurement Science and Technology 2020;31(4):045101 View
  3. Karhade A, Bongers M, Groot O, Kazarian E, Cha T, Fogel H, Hershman S, Tobert D, Schoenfeld A, Bono C, Kang J, Harris M, Schwab J. Natural language processing for automated detection of incidental durotomy. The Spine Journal 2020;20(5):695 View
  4. Toumazis I, Bastani M, Han S, Plevritis S. Risk-Based lung cancer screening: A systematic review. Lung Cancer 2020;147:154 View
  5. Rahmani J, Karimi R, Khani Y, Sabour S. Comment on “Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine”. Journal of Medical Internet Research 2020;22(9):e14944 View
  6. Liu H, Li J, Leng J, Wang H, Liu J, Li W, Liu H, Wang S, Ma J, Chan J, Yu Z, Hu G, Li C, Yang X. Machine learning risk score for prediction of gestational diabetes in early pregnancy in Tianjin, China. Diabetes/Metabolism Research and Reviews 2021;37(5) View
  7. Hu M, Yu G, Shu X, Wu X, Välimäki M, Feng H. Development and validation of a risk prediction model for cognitive impairment among Chinese community-dwelling elders with normal cognition: a machine learning approach (Preprint). Journal of Medical Internet Research 2020 View
  8. Diao X, Huo Y, Yan Z, Wang H, Yuan J, Wang Y, Cai J, Zhao W. An Application of Machine Learning to Etiological Diagnosis of Secondary Hypertension: Retrospective Study Using Electronic Medical Records. JMIR Medical Informatics 2021;9(1):e19739 View
  9. Kats D, Adie Y, Tlimat A, Greco P, Kaelber D, Tarabichi Y. Assessing Different Approaches to Leveraging Historical Smoking Exposure Data to Better Select Lung Cancer Screening Candidates: A Retrospective Validation Study. Nicotine & Tobacco Research 2021;23(8):1334 View
  10. Ribelles N, Alvarez-Lopez I, Arcusa A, Chacon J, de la Haba J, García-Corbacho J, Garcia-Mata J, Jara C, Jerez J, Lázaro-Quintela M, Leon-Mateos L, Ramirez-Merino N, Tibau A, Garcia-Palomo A. Electronic health records and patient registries in medical oncology departments in Spain. Clinical and Translational Oncology 2021;23(10):2099 View
  11. Elkhader J, Elemento O. Artificial intelligence in oncology: From bench to clinic. Seminars in Cancer Biology 2022;84:113 View
  12. Yeh M, Wang Y, Yang H, Bai K, Wang H, Li Y. Artificial Intelligence–Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach. Journal of Medical Internet Research 2021;23(8):e26256 View
  13. Zong N, Ngo V, Stone D, Wen A, Zhao Y, Yu Y, Liu S, Huang M, Wang C, Jiang G. Leveraging Genetic Reports and Electronic Health Records for the Prediction of Primary Cancers: Algorithm Development and Validation Study. JMIR Medical Informatics 2021;9(5):e23586 View
  14. Huang R, Kwon N, Tomizawa Y, Choi A, Hernandez-Boussard T, Hwang J. A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams. JCO Clinical Cancer Informatics 2022;(6) View
  15. Chen A, Lu R, Han R, Huang R, Qin G, Wen J, Li Q, Zhang Z, Jiang W. Building Practical Risk Prediction Models for Nasopharyngeal Carcinoma Screening with Patient Graph Analysis and Machine Learning. Cancer Epidemiology, Biomarkers & Prevention 2023;32(2):274 View
  16. Wang M, Liu Y, Ma Y, Li Y, Sun C, Cheng Y, Cheng P, Liu G, Zhang X. Association Between Cancer Prevalence and Different Socioeconomic Strata in the US: The National Health and Nutrition Examination Survey, 1999–2018. Frontiers in Public Health 2022;10 View
  17. Ladbury C, Amini A, Govindarajan A, Mambetsariev I, Raz D, Massarelli E, Williams T, Rodin A, Salgia R. Integration of artificial intelligence in lung cancer: Rise of the machine. Cell Reports Medicine 2023;4(2):100933 View
  18. Chen A, Chen D. Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data. Scientific Reports 2022;12(1) View
  19. Brown L, Agrawal U, Sullivan F. Using Electronic Medical Records to Identify Potentially Eligible Study Subjects for Lung Cancer Screening with Biomarkers. Cancers 2021;13(21):5449 View
  20. Tai Y, Zhang L, Li Q, Zhu C, Chang V, Rodrigues J, Guizani M. Digital-Twin-Enabled IoMT System for Surgical Simulation Using rAC-GAN. IEEE Internet of Things Journal 2022;9(21):20918 View
  21. Dhiman P, Ma J, Andaur Navarro C, Speich B, Bullock G, Damen J, Hooft L, Kirtley S, Riley R, Van Calster B, Moons K, Collins G. Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review. BMC Medical Research Methodology 2022;22(1) View
  22. Chandran U, Reps J, Yang R, Vachani A, Maldonado F, Kalsekar I. Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer Epidemiology, Biomarkers & Prevention 2023;32(3):337 View
  23. Dhiman P, Ma J, Andaur Navarro C, Speich B, Bullock G, Damen J, Hooft L, Kirtley S, Riley R, Van Calster B, Moons K, Collins G. Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review. Journal of Clinical Epidemiology 2023;157:120 View
  24. Sarnaik K, Linden P, Gasnick A, Bassiri A, Manyak G, Jarrett C, Sinopoli J, Tapias Vargas L, Towe C. Computational risk model for predicting 2-year malignancy of pulmonary nodules using demographic and radiographic characteristics. The Journal of Thoracic and Cardiovascular Surgery 2024;167(6):1910 View
  25. Wang Y, Wei B, Zhao T, Shen H, Liu X, Wang J, Wang Q, Shen R, Feng D. Machine learning-based prediction models for parathyroid carcinoma using pre-surgery cognitive function and clinical features. Scientific Reports 2023;13(1) View
  26. Zhuan B, Ma H, Zhang B, Li P, Wang X, Yuan Q, Yang Z, Xie J. Identification of non-small cell lung cancer with chronic obstructive pulmonary disease using clinical symptoms and routine examination: a retrospective study. Frontiers in Oncology 2023;13 View
  27. Chen H, Wang H, Lin C, Yang R, Lee C. Lung Cancer Prediction Using Electronic Claims Records: A Transformer-Based Approach. IEEE Journal of Biomedical and Health Informatics 2023;27(12):6062 View
  28. Ivaniuk A, Boßelmann C, Zhang X, St. John M, Taylor S, Krishnaswamy G, Milinovich A, Aziz P, Pestana-Knight E, Lal D. Natural language processing and expert follow-up establishes tachycardia association with CDKL5 deficiency disorder. Genetics in Medicine Open 2024;2:100842 View
  29. Chae S, Street W, Ramaraju N, Gilbertson-White S. Prediction of Cancer Symptom Trajectory Using Longitudinal Electronic Health Record Data and Long Short-Term Memory Neural Network. JCO Clinical Cancer Informatics 2024;(8) View
  30. Chapla D, Chorya H, Ishfaq L, Khan A, VR S, Garg S. An Artificial Intelligence (AI)-Integrated Approach to Enhance Early Detection and Personalized Treatment Strategies in Lung Cancer Among Smokers: A Literature Review. Cureus 2024 View
  31. Chen A, Wu E, Huang R, Shen B, Han R, Wen J, Zhang Z, Li Q. Development of Lung Cancer Risk Prediction Machine Learning Models for Equitable Learning Health System: Retrospective Study. JMIR AI 2024;3:e56590 View